Subscribe to this blog

Follow by Email

Search This Blog

Pocket reading stats

Using the same Python code I used to look at my bookmarks, I looked at my reading habits using Pocket and here are the results.

I installed the app in 2014 and therefore, the number of articles I read in 2014 are fewer in number than those I read in 2015. The 2015 numbers should probably be my benchmark from this point on.

These are monthly reading habits. Apparently, I didn't read as much in Feb and March as I did in the following months. Well, I dug myself deep into two of my courses, General Relativity and Ultrafast lasers at that time, which could be the reason. And I might have read less in September/October than in August or November because I was apping those months. Maybe.

Now we come to days of the month. I can't write anything meaningful about this. It'll be better if I get weekly behavior i.e Monday through Sunday and, if I'm correct, see that I read a lot more on Friday/Saturday/Sunday than on the other days of the week.

And we finally come to hourly habits. Note that the time stamps are with respect to GMT and that they need to be corrected given that I live in Chennai (+0530) i.e shift the whole thing left by 5. It makes sense that there are fewer articles in the bins 19-23 as they correspond to just after midnight and just before 6. Something interesting is the dip in bin 10, corresponding to 3/4 PM. This, I don't understand. Maybe it's because i'm mostly out having coffee with friends at that time. I'll have to think about it.

Again, like I've said before, I need to figure out how to get weekly behavior i.e Monday through Sunday. I also want to figure out how to make something similar to Github's commit visualization, which is an awesome way to represent daily activity. So, that's for tomorrow and the coming week I guess.

Get link

Facebook

Twitter

Pinterest

Google+

Email

Labels

Popular posts from this blog

Animation using GNUPlotI've been trying to create an animation depicting a quasar spectrum moving across the 5 SDSS pass bands with respect to redshift. It is important to visualise what emission lines are moving in and out of bands to be able to understand the color-redshift plots and the changes in it.
I've tried doing this using the animate function in matplotlib, python but i wasn't able to make it work - meaning i worked on it for a couple of days and then i gave up, not having found solutions for my problems on the internet.
And then i came across this site, where the gunn-peterson trough and the lyman alpha forest have been depicted - in a beautiful manner. And this got me interested in using js and d3 to do the animations and make it dynamic - using sliders etc.
In the meanwhile, i thought i'd look up and see if there was a way to create animations in gnuplot and whoopdedoo, what do i find but nirvana!

For those of you who don't know, MOOC stands for Massively Open Online Course.

The internet is an awesome thing. It's making education free for all. Well, mostly free. But it's surprising at the width and depth of courses being offered online. And it looks like they are also having an impact on students, especially those from universities that are not top ranked. Students in all parts of the world can now get a first class education experience, thanks to courses offered by Stanford, MIT, Caltech, etc.

I'm talking about MOOCs because one of my new year resolutions is to take online courses, atleast 2 per semester (6 months). And I've chosen the following two courses on edX - Analyzing Big Data with Microsoft R Server and Data Science Essentials for now. I looked at courses on Coursera but I couldn't find any which was worthy and free. There are a lot more MOOC providers out there but let's start here. And I feel like the two courses are relevant to where I …

I just watched this brilliant keynote today. It's a commentary on Programmers and the software development industry/ecosystem as a whole.

I am not going to give you a tl;dr version of the talk because it is a talk that I believe everyone should watch, that everyone should learn from. Instead, I am going to give my own parallel-ish views on programmers and programming.
As pointed out in the talk, there are mythical creatures in the software development industry who are revered as gods. Guido Van Rossum, the creator of Python, was given the title Benevolent Dictator For Life (BDFL). People flock around the creators of popular languages or libraries. They are god-like to most programmers and are treated like gods. By which, I mean to say, we assume they don't have flaws. That they are infallible. That they are perfect.
And alongside this belief in the infallibility of these Gods, we believe that they were born programmers. That programming is something that people are born wit…